Applied Mathematics & Information Sciences

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P. R. China


Image deblurring is a classic problem which has been extensively studied in image processing. The challenge of image deblurring is how to devise efficient and reliable algorithms for recovering the original, sharp image from a blurred and noisy one. In this paper, we consider the implementation of the LSMR method for computing an approximate solution of an ill-posed problem arising from image deblurring. When equipped with a stopping rule based on the discrepancy principle, the LSMR method acts as a regularization method. The numerical examples illustrate that the LSMR method is able to give restored images of higher quality with less computational effort than other widely used regularization methods.

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